Postdoctoral position in deep learning-based methods for dynamic structure determination - Hiring in process/Finished, not possible to apply

The position is shared between Prof. Thomas Schön at the Department of Information Technology and Prof. Johan Elf at the Department of Cell and Molecular Biology (ICM). The collaboration creates prerequisites to develop new deep learning-based methods for studying high-impact biological processes. There are also excellent opportunities to interact with leading research groups in Sweden through our connections in the WASP network (https://wasp-sweden.org/) and within Europe through our connections in the ELLIS network (https://ellis.eu/).

The Department of Information Technology has a prominent position in machine learning research. Thomas Schön develops both theory and applied tools for computer-driven learning, reasoning, and decision making to improve both people's and machines' understanding of real-world complexity. Probabilistic models are central in the research, allowing a systematic representation and managing of the uncertainty inherent in most data. More info Johan Elf's research group at the program for molecular systems biology works interdisciplinary with large-scale genetic engineering and sensitive measurement methods to investigate life at the molecular level. More info: https://elflab.icm.uu.se/

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Duties
You will be responsible for the development of flexible, non-parametric models for the analysis of measurement sequences from several instances of a study object that change over time. In collaboration with researchers at ICM, you will use these models to derive a 4D structure of the bacterial chromosome from image sequences. Such a structure would be imperative for the cell biology research field and answer many outstanding questions regarding the impact of the chromosome structure on gene regulation and microbial physiology and pathology.

This is a full-time research position. You are expected to run your project independently and you have the freedom to develop your ideas within the overall framework of the project. We offer a stimulating interdisciplinary environment where you work closely with experts in deep learning, statistics, signal processing, microbiology, microfluidics, and image analysis. As a postdoctoral fellow at the Department of Information Technology, you will benefit from the strong machine learning research community at Uppsala University. At the same time, the collaboration with ICM provides a good insight into how data is generated and the possibility of influencing the availability of training data.

Requirements
PhD degree in machine learning, signal processing, computational statistics, or related areas or a foreign degree equivalent to a PhD degree in machine learning, signal processing, computational statistics, or related areas. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year frame period is the application deadline. Due to special circumstances, the degree may have been obtained earlier. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

To be eligible for the position, you must have good knowledge in machine learning (especially modelling of dynamic systems), as well as a self-motivated and creative personality and a great interest in basic research. Since the project requires collaboration with researchers both within and outside the group, great social skills are required. You should be able to communicate freely in English.

Additional qualifications
Publications at leading conferences in machine learning are an advantage.

Application
The application must include:

1. A Curriculum Vitae (CV),
2. List of publications,
3. Up to five selected publications in electronic form,
4. Description of your current and previous research (max 1 page) and suggestions for future research (max 1 page),
5. Contact information for two references,
6. A personal letter in which you briefly justify why you are applying for this position and state the earliest possible starting date (max. 1 page).

About the employment
The employment is a temporary position of 2 years according to central collective agreement.  Scope of employment 100 %. Starting date as agreed. Placement: Uppsala.

For further information about the position, please contact: Professor Thomas Schön (phone: +46  18-471 2594, email: thomas.schon@it.uu.se) or Professor Johan Elf (phone: +46 18-471 4678, e-post: johan.elf@icm.uu.se).

Please submit your application by 14 March 2022, UFV-PA 2022/264.

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